Towards a better cancer precision medicine: Systems biology meets immunotherapy

Bhinder, Bhavneet; Elemento, Olivier

doi:10.1016/j.coisb.2017.01.006

“…A Single-Cell Omics Community has recently been founded within ELIXIR (Czarnewski et al, 2022) which we expect to provide us with invaluable collaborations in future. Populating systems biological models with personal data can yield highly individualised models that can help simulate disease evolution and response to therapy with high sensitivity and specificity (Barrette et al, 2018;Béal et al, 2021;Bhinder & Elemento, 2017;Crawford et al, 2018;Eduati et al, 2020;Fey et al, 2015;Hastings et al, 2020). These systems medicine models are knowledge-based and thus able to offer insight into the disease and drug response mechanisms of a patient (Ebata et al, 2022;Hutter & Zenklusen, 2018).…”

Section: Systems Biology Underpinning Systems Medicinementioning

confidence: 99%

Systems Biology in ELIXIR: modelling in the spotlight

Martins dos Santos,

Anton,

Szomolay

et al. 2024

F1000Res

0

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In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR’s future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

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“…A prominent example is The Cancer Genome Atlas , an enormous repository of multi-omics data from over 11,000 cases across 33 cancer types ( Hutter & Zenklusen, 2018 ). Populating systems biological models with personal data can yield highly individualised models that can help simulate disease evolution and response to therapy with high sensitivity and specificity ( Barrette et al , 2018 ; Béal et al , 2021 ; Bhinder & Elemento, 2017 ; Crawford et al , 2018 ; Eduati et al , 2020 ; Fey et al , 2015 ; Hastings et al , 2020 ). These systems medicine models are knowledge-based and thus able to offer insight into the disease and drug response mechanisms of a patient ( Hutter & Zenklusen, 2018 ; Ebata et al , 2022 ).…”

Section: Developing An Elixir Systems Biology Roadmapmentioning

confidence: 99%

Systems Biology in ELIXIR: modelling in the spotlight

Anton

¹

,

Szomolay

²

,

Ostaszewski

³

et al. 2022

F1000Res

3

0

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In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR’s future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

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“…The potential for systems biology approaches to improve efforts to personalise treatments for cancer patients is a consistent motif throughout the literature relating to this topic (Bhinder & Elemento, 2017;Filipp, 2017;Frantzi, Bhat, & Latosinska, 2014;Saez-Rodriguez & Bluthgen, 2020). Contrasting with the use of artificial intelligence machine-learning algorithms which can be used to personalised treatments plans based on correlations drawn from large volumes of data, with a systems biology approach we attempt to determine the molecular mechanisms that drive the disease (Fountzilas & Tsimberidou, 2018).…”

Section: Systems Biologymentioning

confidence: 99%